text model · Mistral · iOS
Can I run Ministral 3 3B on iPhone 17?
Yes. Ministral 3 3B runs on iPhone 17 at Q4_K_M (~3.2 GB of ~4.5 GB usable).
Runs at Q4_K_M using ~3.2 GB of ~4.5 GB usable.
That figure is at a 4k context and moves about ±15% as context length changes. iPhone 17 leaves ~1.3 GB of headroom.
- Q4_K_M needed
- ~3.2 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 GB
- Best quant
- Q4_K_M
Which quant fits
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).
- Parameters
- 3B
- Q4_K_M size
- 2 GB
- Q8_0 size
- 3.4 GB
- Context
- 256k
- Ollama tag
- ministral-3:3b
- Memory
- 8 GB unified
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
You could also run
Run Ministral 3 3B on other hardware
FAQ
Can iPhone 17 run Ministral 3 3B?
Yes. Ministral 3 3B runs on iPhone 17 at Q4_K_M (~3.2 GB of ~4.5 GB usable).
How much memory does Ministral 3 3B need?
iPhone 17 has room to spare. At Q4_K_M the weights are ~2 GB; with KV cache and runtime overhead, budget ~3.2 GB at a 4k context.
What is the best tool to run Ministral 3 3B on iOS?
On iPhone and iPad, Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.) is the standard choice. Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/ministral-3-3b/iphone-17) Sources
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apple.com · 1 source
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developer.apple.com · 1 source
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en.wikipedia.org · 2 sources
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enclaveai.app · 1 source
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github.com · 3 sources
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huggingface.co · 2 sources
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layla-network.ai · 1 source
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macrumors.com · 1 source
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ollama.com · 1 source
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privatellm.app · 1 source
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.